Coordination degree and driving factors of water resources utilization efficiency and ecological resilience in China

doi:10.3969/j.issn.1004-9479.2025.02.20230240

Abstract

Abstract:

Clarifying the coordination relationship between water resources utilization efficiency and ecological resilience in China is a positive response to the construction of ecological civilization in the new era and the Chinese modernization featuring harmonious coexistence between man and nature. This paper took 30 provinces (municipalities and districts) in mainland China as the research object, used the coordination degree model, kernel density estimation, GIS spatial analysis,and spatial Markov chain to comprehensively analyze the temporal evolution, spatial distribution,and state transition trends of coordination degree between water resources utilization efficiency and ecological resilience in China from 2008 to 2020, as well as introduced the spatial lag Tobit model to explore the driving factors. The results show that: (1) From the perspective of temporal evolution, the coordination degree presents continuous growth trend, but the absolute difference between regions expands. From the perspective of spatial distribution, the coordination degree presents a gradient descending pattern of "east-central-west", and the high-value area is mainly concentrated in the eastern coastal area. (2) The state transfer of coordination degree has club convergence characteristics, and the convergence effect is more obvious in the middle-level and high-level areas. When the coordination degree of neighbors is higher than that of the local area, the positive spatial spillover effect can play a role, and the spillover effect becomes more prominent with improving coordination degree of neighbors. (3) Endogenous power is the main driving force for the improvement of coordination degree in our country, while government power and exogenous power have the problem of insufficient development. There is heterogeneity in the driving factors across regions, with endogenous power dominating in the east and west, while government power and exogenous power significantly contribute to the improvement of coordination in the central region.

Key words: water resources utilization efficiency, ecological resilience, coordination degree, spatial-temporal evolution, driving forces

摘要：

明晰中国水资源利用效率与生态韧性的协调关系，是对新时代生态文明建设以及人与自然和谐共生的中国式现代化的积极响应。以中国大陆30个省（市、区）为研究对象，运用协调度模型、核密度估计、GIS空间分析和空间马尔可夫链等方法，对2008—2020年我国水资源利用效率与生态韧性协调度的时序演变、空间分布及状态转移趋势进行全面分析，并引入空间滞后Tobit模型探究其动力因素。结果表明：①水资源利用效率与生态韧性协调度整体呈持续增长态势，但区域间的绝对差异有所扩大，空间上呈现“东-中-西”梯度递减格局，高值区集聚在东部沿海地区。②水资源利用效率与生态韧性协调度的状态转移存在俱乐部收敛特征；中高及高水平地区趋同效应更为明显；当邻地协调度高于本地时，正向空间溢出效应得以发挥，随着邻地协调度提升，溢出效应更为突出。③内源动力是我国水资源利用效率与生态韧性协调度提升的主要动力，政府动力和外向动力之间存在开发不充分的问题；各地区动力因素存在异质性，东、西部地区内源动力占据主导，而政府动力与外向动力在中部地区则显著促进了协调度的提升。

关键词: 水资源利用效率, 生态韧性, 协调度, 时空演变, 动力因素

Mingdou ZHANG, Yanting REN, Yaobin LIU. Coordination degree and driving factors of water resources utilization efficiency and ecological resilience in China[J]. World Regional Studies, 2025, 34(2): 168-180.

张明斗, 任衍婷, 刘耀彬. 中国水资源利用效率与生态韧性的协调度及动力因素研究[J]. 世界地理研究, 2025, 34(2): 168-180.

Figures/Tables 8

Fig.1 Framework of the coordination mechanism between water resource utilization efficiency and ecological resilience

Tab.1 Evaluation index system of ecological resilience

目标层	准则层	指标层	指标含义	符号	权重
生态韧性	压力	单位GDP工业二氧化硫排放量/（t/万元）	废气排放强度	—	0.033
		单位GDP综合能耗/（t标准煤/万元）	能源消耗强度	—	0.077
		单位GDP建设用地占用面积/（km²/万元）	地区地耗强度	—	0.052
	状态	人均公园绿地面积/m²	生态宜居空间	+	0.188
	状态	建成区绿化覆盖率/%	地区绿化水平	+	0.089
	响应	工业固体废物综合利用率/%	废物综合利用	+	0.211
		污水处理厂集中处理率/%	环境治理响应	+	0.082
		生活垃圾无害化处理率/%	人居环境改善	+	0.072
		环保支出占财政支出比重/%	环保投入强度	+	0.196

Tab.2 Coordination degree grade standard

协调度	协调等级	协调区间
[0.0, 0.1]	极度失调	不可接受区间
(0.1, 0.2]	严重失调
(0.2, 0.3]	中度失调
(0.3, 0.4]	轻度失调
(0.4, 0.5]	濒临失调	勉强接受区间
(0.5, 0.6]	勉强协调	勉强接受区间
(0.6, 0.7]	初级协调	可接受区间
(0.7, 0.8]	中级协调
(0.8, 0.9]	良好协调
(0.9, 1.0]	优质协调

Fig.2 Kernel density estimation distribution of coordination degree

Fig.3 Spatial distribution pattern of coordination degree

Tab.3 Spatial Markov transfer probability matrix of coordination degree

滞后类型	t/t+1	低	中低	中高	高
无	低	0.735	0.265	0.000	0.000
	中低	0.000	0.729	0.271	0.000
	中高	0.000	0.000	0.773	0.227
	高	0.000	0.000	0.000	1.000
低	低	0.809	0.191	0.000	0.000
	中低	0.000	0.923	0.077	0.000
	中高	0.000	0.000	1.000	0.000
	高	NaN	NaN	NaN	NaN
中低	低	0.593	0.407	0.000	0.000
	中低	0.000	0.739	0.261	0.000
	中高	0.000	0.000	0.810	0.190
	高	0.000	0.000	0.000	1.000
中高	低	0.333	0.667	0.000	0.000
	中低	0.000	0.676	0.324	0.000
	中高	0.000	0.000	0.792	0.208
	高	0.000	0.000	0.000	1.000
高	低	NaN	NaN	NaN	NaN
	中低	0.000	0.333	0.667	0.000
	中高	0.000	0.000	0.625	0.375
	高	0.000	0.000	0.000	1.000

Tab.4 Driving forces setting of coordination degree

动力类型	变量名称	变量符号	变量说明	VIF
内源动力	经济发展水平	ECO	人均GDP取对数	3.28
	技术创新水平	TEC	规模以上工业企业R&D经费支出取对数	2.02
	产业结构升级水平	IND	第三产业增加值/第二产业增加值	2.96
政府动力	政府干预水平	GOV	政府农林水务支出/一般预算支出	2.73
外向动力	对外开放水平	OPEN	进出口额/GDP	2.86

Tab.5 Regression results of driving forces of coordination degree

ECO

0.083^***

(6.190)

0.095^***

(7.660)

0.193^***

(19.890)

0.161^***

(21.280)

0.164^***

(10.380)

0.160^***

(10.020)

0.129^***

(14.500)

TEC

0.028^***

(5.020)

0.024^***

(5.380)

0.026^***

(4.820)

0.017^***

(5.310)

0.011^**

(2.420)

0.056^***

(6.560)

0.026^***

(5.650)

IND

－0.002

(－0.240)

0.009

(1.580)

0.031^***

(4.980)

0.041^***

(9.130)

0.032^***

(4.920)

0.019

(1.280)

0.128^***

(8.810)

GOV

－0.102

(－1.380)

－0.143^*

(－1.930)

－0.188^**

(－2.200)

－0.158

(－1.410)

－0.960^***

(－3.850)

0.684^***

(3.500)

－0.305^**

(－2.110)

OPEN

－0.040^***

(－3.220)

－0.026^**

(－2.360)

－0.062^***

(－4.950)

－0.050^***

(－3.820)

－0.117^***

(－6.290)

0.247^***

(3.170)

0.001

(0.020)

_CONS

－1.013^***

(－12.180)

－1.804^***

(－41.970)

－1.372^***

(－22.560)

－1.190^***

(－8.040)

－1.985^***

(－17.650)

－1.268^***

(－18.700)

ρ

0.501^***

(10.700)

0.453^***

(10.540)

0.011^***

(4.030)

0.005

(0.720)

0.027^***

(－4.030)

0.023^***

(5.300)

R²

Adj-R²

Tab.5 Regression results of driving forces of coordination degree

变量

（1）

（2）

（3）

（4）

（5）

（6）

（7）

固定效应空间滞后模型

随机效应空间滞后模型

Tobit模型

空间滞后Tobit模型

东部

中部

西部

ECO

0.083^***

(6.190)

0.095^***

(7.660)

0.193^***

(19.890)

0.161^***

(21.280)

0.164^***

(10.380)

0.160^***

(10.020)

0.129^***

(14.500)

TEC

0.028^***

(5.020)

0.024^***

(5.380)

0.026^***

(4.820)

0.017^***

(5.310)

0.011^**

(2.420)

0.056^***

(6.560)

0.026^***

(5.650)

IND

－0.002

(－0.240)

0.009

(1.580)

0.031^***

(4.980)

0.041^***

(9.130)

0.032^***

(4.920)

0.019

(1.280)

0.128^***

(8.810)

GOV

－0.102

(－1.380)

－0.143^*

(－1.930)

－0.188^**

(－2.200)

－0.158

(－1.410)

－0.960^***

(－3.850)

0.684^***

(3.500)

－0.305^**

(－2.110)

OPEN

－0.040^***

(－3.220)

－0.026^**

(－2.360)

－0.062^***

(－4.950)

－0.050^***

(－3.820)

－0.117^***

(－6.290)

0.247^***

(3.170)

0.001

(0.020)

_CONS

－1.013^***

(－12.180)

－1.804^***

(－41.970)

－1.372^***

(－22.560)

－1.190^***

(－8.040)

－1.985^***

(－17.650)

－1.268^***

(－18.700)

ρ

0.501^***

(10.700)

0.453^***

(10.540)

0.011^***

(4.030)

0.005

(0.720)

0.027^***

(－4.030)

0.023^***

(5.300)

R²

0.951

0.954

0.963

0.943

0.961

0.949

Adj-R²

0.959

0.936

0.955

0.943

References 33

1	丁绪辉, 贺菊花, 王柳元. 考虑非合意产出的省际水资源利用效率及驱动因素研究——基于SE-SBM与Tobit模型的考察. 中国人口·资源与环境, 2018, 28(1): 157-164.
	DING X, HE J, WANG L. Inter-provincial water resources utilization efficiency and its driving factors considering undesirable outputs——Based on SE-SBM and Tobit model. China Population, Resources and Environment, 2018, 28(1): 157-164.
2	钱文婧, 贺灿飞. 中国水资源利用效率区域差异及影响因素研究. 中国人口·资源与环境, 2011, 21(2): 54-60.
	QIAN W, HE C. China's regional difference of water resource use efficiency and influencing factors. China Population, Resources and Environment, 2011, 21(2): 54-60.
3	SONG M, WANG R, ZENG X.Water resources utilization efficiency and influence factors under environmental restrictions. Journal of Cleaner Production, 2018, 184(5): 611-621.
4	陈艳萍, 刘畅. 中国水资源利用效率及其影响因素研究——基于Shephard水资源距离函数. 世界地理研究, 2022, 31(3): 591-601.
	CHEN Y, LIU C. Research on water resources utilization efficiency and its influencing factors in China——Based on Shephard water resources distance function. World Regional Studies, 2022, 31(3): 591-601.
5	钞锦龙, 李乐乐, 杨朔, 等. 汾河流域城市化与水资源耦合协调关系研究. 地理科学, 2022, 42(3): 487-496.
	CHAO J, LI L, YANG S, et al. Coupling and coordination relationship between urbanization and water resources in the Fenhe River Basin. Scientia Geographica Sinica, 2022, 42(3): 487-496.
6	LI W, HAI X, HAN L, et al. Does urbanization intensify regional water scarcity?Evidence and implications from a megaregion of China. Journal of Cleaner Production, 2020, 244: 118592.
7	焦士兴, 王安周, 张馨歆, 等. 经济新常态下河南省产业结构与水资源耦合协调发展研究. 世界地理研究, 2020, 29(2): 358-365.
	JIAO S, WANG A, ZHANG X, et al. Coordinated development of industrial structure and water resources in Henan Province under the "New Normal". World Regional Studies, 2020, 29(2): 358-365.
8	杨胜苏, 张利国, 喻玲, 等. 湖南省社会经济与水资源利用协调发展演化. 经济地理, 2020, 40(11): 86-94.
	YANG S, ZHANG L, YU L, et al. The coordinated development and evolution of social economy and water resources utilization in Hunan Province. Economic Geography, 2020, 40(11): 86-94.
9	盖美, 王宇飞, 马国栋, 等. 辽宁沿海地区用水效率与经济的耦合协调发展评价. 自然资源学报, 2013, 28(12): 2081-2094.
	GAI M, WANG Y, MA G, et al. Evaluation of the coupling coordination development between water use efficiency and economy in Liaoning coastal Economic Belt. Journal of Natural Resources, 2013, 28(12): 2081-2094.
10	WANG S, YANG J, WANG A, et al. Coupled coordination of water resources-economy-ecosystem complex in the Henan section of the Yellow River Basin. Water Supply, 2022, 22(12): 8835-8848.
11	ZHOU R, JIN J, WU C, et al. Connection number based model for coordination development evaluation of regional water resources, social economy and ecological environment complex system. Journal of Environmental Management, 2023, 339: 117913.
12	王松茂, 牛金兰. 山东半岛城市群城市生态韧性的动态演化及障碍因子分析. 经济地理, 2022, 42(8): 51-61.
	WANG S, NIU J. Dynamic evolution and obstacle factors of urban ecological resilience in Shandong Peninsula Urban Agglomeration. Economic Geography, 2022, 42(8): 51-61.
13	ALBERTI M, MARZLUFF J, SHULENBERGER E, et al. Integrating humans into ecology: Opportunities and challenges for studying urban ecosystems. BioScience, 2003, 53(12): 1169-1179.
14	吕添贵, 胡晗, 付舒斐, 等. 长三角地区城市生态韧性时空分异特征及影响因素. 地域研究与开发, 2023, 42(1): 54-60.
	LYU T, HU H, FU S, et al. Spatio-temporal differentiation and influencing factors of urban ecological resilience in the Yangtze River Delta. Areal Research and Development, 2023, 42(1): 54-60.
15	SHI C, ZHU X, WU H, et al. Assessment of urban ecological resilience and its influencing factors: A case study of the Beijing-Tianjin-Hebei Urban Agglomeration of China. Land, 2022, 11(6): 921.
16	王少剑, 崔子恬, 林靖杰, 等. 珠三角地区城镇化与生态韧性的耦合协调研究. 地理学报, 2021, 76(4): 973-991.
	WANG S, CUI Z, LIN J, et al. Coupling relationship between urbanization and ecological resilience in the Pearl River Delta. Acta Geographica Sinica, 2021, 76(4): 973-991.
17	薛明月. 黄河流域经济发展与生态环境耦合协调的时空格局研究. 世界地理研究, 2022, 31(6): 1261-1272.
	XUE M. The spatial and temporal pattern of coupling and coordination between economic development and ecological environment in the Yellow River Basin.World Regional Studies, 2022, 31(6): 1261-1272.
18	XU X, WANG M, WANG M, et al. The coupling coordination degree of economic, social and ecological resilience of Urban Agglomerations in China. International Journal of Environmental Research and Public Health, 2022, 20(1): 413.
19	LIN Y, PENG C, CHEN P, et al. Conflict or synergy?Analysis of economic-social- infrastructure-ecological resilience and their coupling coordination in the Yangtze River Economic Belt, China. Ecological Indicators, 2022, 142: 109194.
20	XIE X, FANG B, XU H, et al. Study on the coordinated relationship between urban land use efficiency and ecosystem health in China. Land Use Policy, 2021, 102: 105235.
21	陶倩, 兰安军, 范泽孟, 等. 长三角城市群城市韧性与城市土地利用效益的耦合协调性分析.水土保持研究,2023, 30(4): 373-383.
	TAO Q, LAN A, FAN Z, et al. Coupling coordination analysis of urban resilience and urban land use efficiency in Urban Agglomeration of Yangtze River Delta.Research of Soil and Water Conservation,2023,30(4): 373-383.
22	陶洁怡, 董平, 陆玉麒. 长三角地区生态韧性时空变化及影响因素分析. 长江流域资源与环境, 2022, 31(9): 1975-1987.
	TAO J, DONG P, LU Y. Spatial-temporal analysis and influencing factors of ecological resilience in Yangtze River Delta. Resources and Environment in the Yangtze Basin, 2022, 31(9): 1975-1987.
23	李阳力, 陈天, 臧鑫宇. 围水定策——中国31个省份水生态韧性评价与优化战略思考. 中国软科学, 2022, 378(6): 96-110.
	LI Y, CHEN T, ZANG X. Strategic thinking and evaluation of water-ecological resilience——A case study of 31 provinces, autonomous regions and cities in China. China Soft Science, 2022, 378(6): 96-110.
24	黄梅, 刘晨曦, 俞晓莹, 等. 城市水生态网络韧性评价与优化策略——以长沙市为例. 经济地理, 2022, 42(10): 52-60.
	HUANG M, LIU C, YU X, et al. Resilience evaluation and optimization of urban water ecological network——Take Changsha as an example. Economic Geography, 2022, 42(10): 52-60.
25	陈天, 石川淼, 王高远. 气候变化背景下的城市水环境韧性规划研究——以新加坡为例. 国际城市规划, 2021, 36(5):52-60.
	CHEN T, SHI C, WANG G. Research on urban water environment resilience planning under the background of climate change——A case study of Singapore. Urban Planning International, 2021, 36(5): 52-60.
26	张军, 吴桂英, 张吉鹏. 中国省际物质资本存量估算: 1952—2000. 经济研究, 2004, 50(10): 35-44.
	ZHANG J, WU G, ZHANG J. The estimation of China's provincial capital stock: 1952—2000. Economic Research Journal, 2004, 50(10): 35-44.
27	ZHAO R, FANG C, LIU H, et al. Evaluating urban ecosystem resilience using the DPSIR framework and the ENA model: A case study of 35 cities in China. Sustainable Cities and Society, 2021, 72(4): 102997.
28	肖黎明,张仙鹏.强可持续理念下绿色创新效率与生态福利绩效耦合协调的时空特征.自然资源学报,2019,34(2): 312-324.
	XIAO L, ZHANG X.Spatio-temporal characteristics of coupling coordination between green innovation efficiency and ecological welfare performance under the concept of strong sustainability. Journal of Natural Resources, 2019, 34(2): 312-324.
29	王银银, 杨俊文, 开燕华. 中国沿海城市海洋经济密度时空变迁与趋同演化研究. 经济问题, 2021(1): 87-96.
	WANG Y, YANG J, KAI Y. Spatial and temporal changes and convergence evolution of marine economic density in China's coastal cities. On Economic Problems, 2021(1): 87-96.
30	穆学青, 郭向阳, 明庆忠, 等. 黄河流域旅游生态安全的动态演变特征及驱动因素. 地理学报, 2022, 77(3): 714-735.
	MU X, GUO X, MING Q, et al. Dynamic evolution characteristics and driving factors of tourism ecological security in the Yellow River Basin. Acta Geographica Sinica, 2022, 77(3): 714-735.
31	张国兴, 张婧钰, 周桂芳. 黄河流域资源型城市生态安全等级边界及演化趋势. 资源科学, 2023, 45(4): 762-775.
	ZHANG G, ZHANG J, ZHOU G. Ecological security level of resource-based cities in the Yellow River Basin and trend of change. Resources Science, 2023, 45(4): 762-775.
32	陈磊, 吴继贵, 王应明. 基于空间视角的水资源经济环境效率评价. 地理科学, 2015, 35(12): 1568-1574.
	CHEN L, WU J, WANG Y. Efficiency evaluation of water resource-economic-environment system based on spatial perspective. Scientia Geographica Sinica, 2015, 35(12): 1568-1574.
33	邓宗兵, 宗树伟, 苏聪文, 等. 长江经济带生态文明建设与新型城镇化耦合协调发展及动力因素研究. 经济地理, 2019, 39(10): 78-86.
	DENG Z, ZONG S, SU C, et al. Research on coupling coordination development between ecological civilization construction and new urbanization and its driving forces in the Yangtze River Economic Zone. Economic Geography, 2019, 39(10): 78-86.

[1]	Yi WANG, Shuya CAI, Xiaoting LI, Yuqi LU. Is the "Impossible Triangle" of the energy in China really impossible? An empirical test based on Coupling Coordination Degree Model [J]. World Regional Studies, 2024, 33(8): 87-101.
[2]	Xin CHEN, Jiabei ZHOU, Yuantao LIAO, Shaojian WANG. Coupling evolution and influencing factors of carbon emissions-urban high quality development level in Yangtze River Delta [J]. World Regional Studies, 2024, 33(3): 103-115.
[3]	Mingxing QI, Shuang CHEN. Coupling and coordinating relationships between urbanization and infrastructure in the countries around Lake Victoria, Africa [J]. World Regional Studies, 2023, 32(5): 34-45.
[4]	Zaijun LI, Meijuan HU. Spatial-temporal evolution and formation mechanism of ecological well-being performance in Jiangsu Province [J]. World Regional Studies, 2023, 32(3): 124-135.
[5]	Chang LU, Xueyuan XU, Meixuan ZHOU. Analysis on coupling coordination degree of production-living-ecological functions in shrinking cities of China's three major urban agglomerations [J]. World Regional Studies, 2023, 32(3): 76-88.
[6]	Yu WANG, Jinxiang ZHANG, Yujie WANG, Jieying YANG. Influence mechanism and measurement of "institutional distance" of administrative regions in regional economic integration: [J]. World Regional Studies, 2023, 32(11): 141-154.
[7]	Laishun WANG, Jianzhong LIU, Yinbao ZHANG, Xinjia ZHANG. Spatial-temporal evolution of green trade pattern in countries along "the 21st Century Maritime Silk Road" [J]. World Regional Studies, 2023, 32(10): 63-75.
[8]	Na SONG, Yaqi MAO, Yali HE, Yibo TANG. A study on the coupling and coordination of tourism space among four provinces and cities in the Yangtze River Delta from the perspective of three-dimensional space [J]. World Regional Studies, 2023, 32(1): 104-116.
[9]	Hui LI, Qilong REN, Chunmei ZHANG. Study on the spatial-temporal evolution and driving factors of urban logistics links in Beijing-Tianjin-Hebei Region [J]. World Regional Studies, 2022, 31(5): 1046-1056.
[10]	Xiang KONG, Kaihang CHEN, Yiman LI. The temporal and spatial evolution of market segmentation and its spatial spillover in the Yangtze River Delta Region [J]. World Regional Studies, 2022, 31(4): 827-836.
[11]	Ping WANG, Yan CHEN, Yeqing CHENG, Jiehua SONG. Evolution and driving mechanism of urban-rural relationship in Hainan Province [J]. World Regional Studies, 2022, 31(4): 849-861.
[12]	Heng LI, Yan HAN. Analysis on the spatial-temporal evolution characteristics of PM_2.5 and its influencing factors in the Yellow River Basin [J]. World Regional Studies, 2022, 31(1): 130-141.
[13]	Yang YANG, Xiaolan TANG, Yanyan JIA, Qiaoqiao Zhan. Spatial-temporal coupling coordination degree and driving factors of population, land and economy urbanization in the Yangtze Basin [J]. World Regional Studies, 2021, 30(5): 978-990.
[14]	Ailian HUANG, Junrong ZHU, Pingyu LUO. Research on the relationship between border tourism and border trade based on coupled coordination model: A case study of Dongxing [J]. World Regional Studies, 2021, 30(3): 657-666.
[15]	Feiyu LU, Weihua YIN, Nannan LIU. The spatio-temporal evolution of industrial resilience and its driving factors in the Yangtze River Delta Urban Agglomeration [J]. World Regional Studies, 2021, 30(3): 589-600.